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dc.contributorUniversitat Ramon Llull. IQS
dc.contributor.authorCano-Lara, Miroslava
dc.contributor.authorLópez, Adolfo R.
dc.contributor.authorRostro Gonzalez, Horacio
dc.contributor.authorPadilla-Medina, José Alfredo
dc.contributor.authorBarranco-Gutiérrez, Alejandro Israel
dc.date.accessioned2024-11-30T08:11:47Z
dc.date.available2024-11-30T08:11:47Z
dc.date.issued2024-07-08
dc.identifier.issn2076-3417ca
dc.identifier.urihttp://hdl.handle.net/20.500.14342/4587
dc.description.abstractThe orange (Citrus sinensis) is a fruit of the Citrus genus, which is part of the Rutaceae family. The orange has gained considerable importance due to its extensive range of applications, including the production of juices, jams, sweets, and extracts. The consumption of oranges confers several nutritional benefits, including flavonoids, vitamin C, potassium, beta-carotene, and dietary fiber. It is crucial to acknowledge that the primary quality criterion employed by consumers and producers is maturity, which is correlated with the visual quality associated with the color of the epicarp. This study proposes the implementation of a computer vision system that estimates the degree of ripeness of oranges Valencia using fuzzy logic (FL); the soluble solids content was determined by refractometry, while the firmness of the fruit was evaluated through the fruit firmness test. The proposed method was divided into five distinct steps. The initial stage involved the acquisition of RGB images. The second stage presents the segmentation of the fruit, which entails the removal of extraneous noise and backgrounds. The third and fourth steps involve determining the centroid of the fruit, and five regions of interest were obtained in the centroid of the fruit of the Citrus Color Index (CII), ranging from 3 × 3 to 11 × 11 pixels. Finally, in the fifth step, a model was created to estimate maturity, °Brix, and firmness using Matlab 2024 and the Fuzzy Logic Designer and Neuro-Fuzzy Designer applications. Consequently, a statistically significant correlation was established between maturity, degree Brix, and firmness, with a value greater than 0.9, using the Citrus Color Index (CII), which reflects the physical–chemical changes that occur in the orange.ca
dc.format.extent18 p.ca
dc.language.isoengca
dc.publisherMDPIca
dc.relation.ispartofApplied Sciences. 2024;14(13):5953-5971ca
dc.rights© L'autor/aca
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherCitrus Color Index (CII)ca
dc.subject.otherdegree Brixca
dc.subject.otherfirmnessca
dc.subject.otherfuzzy logic (FL)ca
dc.subject.othermaturityca
dc.subject.otherorangeca
dc.titleFuzzy Classification of the Maturity of the Orange (Citrus × sinensis) Using the Citrus Color Index (CCI)ca
dc.typeinfo:eu-repo/semantics/articleca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.subject.udc5ca
dc.identifier.doihttps://doi.org/10.3390/app14135953ca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca


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